Abstract
One approach to delaying the spread of the novel coronavirus (COVID-19) is to reduce human travel by imposing travel restriction policies. Understanding the actual human mobility response to such policies remains a challenge owing to the lack of an observed and large-scale dataset describing human mobility during the pandemic. This study uses an integrated dataset, consisting of anonymized and privacy-protected location data from over 150 million monthly active samples in the USA, COVID-19 case data and census population information, to uncover mobility changes during COVID-19 and under the stay-at-home state orders in the USA. The study successfully quantifies human mobility responses with three important metrics: daily average number of trips per person; daily average person-miles travelled; and daily percentage of residents staying at home. The data analytics reveal a spontaneous mobility reduction that occurred regardless of government actions and a ‘floor’ phenomenon, where human mobility reached a lower bound and stopped decreasing soon after each state announced the stay-at-home order. A set of longitudinal models is then developed and confirms that the states' stay-at-home policies have only led to about a 5% reduction in average daily human mobility. Lessons learned from the data analytics and longitudinal models offer valuable insights for government actions in preparation for another COVID-19 surge or another virus outbreak in the future.
Highlights
The 2019 coronavirus disease (COVID-19) pandemic is undoubtedly one of the worst global health crises seen in decades
To quantify how people in different states responded to stayat-home state orders during the COVID-19 pandemic, we studied the longitudinal changes in state-level mobility using a generalized additive model (GAM) [31,32] of the daily average number of trips per person and daily average person-miles travelled (PMT)
Interface 17: 20200344 models daily average number of trips per person daily average person-miles travelled parametric coefficients stay-at-home order issued without penalty or without specifying enforcement stay-at-home order issued and enforced with warning, and possible fine for repeated offence stay-at-home order issued and enforced with fine and possible jail time daily number of newly confirmed coronavirus cases in the states (1000) daily number of newly confirmed coronavirus cases in the adjacent states (1000) daily number of newly confirmed coronavirus cases in the USA (1000) state governor approval rate (%) weekend approximate significance of smooth terms s s s s s
Summary
The 2019 coronavirus disease (COVID-19) pandemic is undoubtedly one of the worst global health crises seen in decades. The first confirmed case of COVID19 in the USA emerged in Washington State on 21 January 2020. The US government proclaimed a national state of emergency on 13 March 2020. Following an exponential growth in the number of confirmed cases, the Federal Emergency Management Agency (FEMA) announced its first major disaster in the state of New York on 20 March 2020, followed by California and Washington on 22 March [1]. As of 11 April 2020, FEMA had announced that the COVID-19 pandemic was a disaster in every state, with Wyoming being the last one. On 19 March 2020, California became the first state to institute a stay-at-home or shelter-in-place order [2]. Three of the eight states had partial stay-at-home orders, implemented by city mayors or county executives [3]
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